rxmc#

rxmc is an orchestration layer for Bayesian calibration of reaction models to large data sets with flexible likelihood modeling.

It is built around two complementary workflows:

  1. External-sampler orchestration via CalibrationConfig for drivers such as black-box-bayes.

  2. In-package end-to-end prototyping via Walker for smaller problems where you want to run the full MCMC workflow locally.

The package composes curated experimental data (Observation), model predictions (PhysicalModel), statistical assumptions (LikelihoodModel), independent data-model pairings (Constraint), and full calibration problems (Evidence).

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